A bare-hand gesture interaction system for virtual environments

Hand-based gestures provide direct mappings of user actions to 3D UI tasks; they are becoming a more attractive interaction alternative than keyboards, mice, controllers, among others. In this paper, we present a fast algorithm for hand gesture recognition for interaction in virtual environments. The method applies mathematical morphology operators (binarization and dilation) to acquire a clean segmented hand image from a depth data stream on which a curvature-metric and K-means algorithm is applied to detect the fingertips, then using fingertip and palm positions together with anthropomorphic metrics and a rule based system we perform gesture recognition. In addition, the intermittence gesture spotting problem is reduced using a digital integrator. Finally, a set of virtual environments were designed to demonstrate the performance, reliability and feasibility of our method.